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cs.LG2025
TT-Prune: Joint Model Pruning and Resource Allocation for Communication-efficient Time-triggered Federated Learning
Xinlu Zhang, Yansha Deng, Toktam Mahmoodi
Federated learning (FL) offers new opportunities in machine learning, particularly in addressing data privacy concerns. In contrast to conventional event-based federated learning,…
cs.LG2025★ 1 cited
Communication-Aware Knowledge Distillation for Federated LLM Fine-Tuning over Wireless Networks
Xinlu Zhang, Na Yan, Yang Su +2
Federated learning (FL) for large language models (LLMs) offers a privacy-preserving scheme, enabling clients to collaboratively fine-tune locally deployed LLMs or smaller language…
cs.LG2024★ 1 cited
Joint Model Pruning and Resource Allocation for Wireless Time-triggered Federated Learning
Xinlu Zhang, Yansha Deng, Toktam Mahmoodi
Time-triggered federated learning, in contrast to conventional event-based federated learning, organizes users into tiers based on fixed time intervals. However, this network still…